Some notes to self on document layout analysis. I’m revisiting the problem of taking a PDF or a scanned document and determining its structure (for example, where is the title, abstract, bibliography, where are the figures and their captions, etc.). There are lots of papers on this topic, and lots of tools.
GBIF recently released the Phylogeny Explorer, using legumes as an example dataset. The goal is to enables users to “view occurrence data from the GBIF network aligned to legume phylogeny.” The screenshot below shows the legume phylogeny side-by-side with GBIF data.
Recently I’ve been messing about with DNA barcodes. I’m junior author with David Schindel on forthcoming book chapter Creating Virtuous Cycles for DNA Barcoding: A Case Study in Science Innovation, Entrepreneurship, and Diplomacy, and I’ve blogged about Adventures in machine learning: iNaturalist, DNA barcodes, and Lepidoptera. One thing I’ve always wanted is a simple way to explore DNA barcodes both geographically and phylogenetically.
To much fanfare BiCIKL launched the “Biodiversity Knowledge Hub” (see Biodiversity Knowledge Hub is online!!!). This is advertised as a “game-changer in scientific research”. The snappy video in the launch tweet claims that the hub will it will help your research thanks to interlinked data… …and responds to complex queries with the services provided… Interlinked data, complex queries, this all sounds very impressive.
Recently I’ve been working with a masters student, Maja Nagler, on a project using machine learning to identify images of Lepidoptera. This has been something of an adventure as I am new to machine learning, and have only minimal experience with the Python programming language. So what could possibly go wrong?
Tony Rees commented on my recent post Ten years and a million links. I’ve responded to some of his comments, but I think the bigger question deserves more space, hence this blog post. Tony’s comment Hi Rod, I like what you’re doing.
As trailed on a Twitter thread last week I’ve been working on a manuscript describing the efforts to map taxonomic names to their original descriptions in the taxonomic literature.
Some quick notes on interface ideas for digital libraries and/or knowledge graphs. Recently there’s been something of an explosion in bibliographic tools to explore the literature.
One thing about ChatGPT is it has opened my eyes to some concepts I was dimly aware of but am only now beginning to fully appreciate. ChatGPT enables you ask it questions, but the answers depend on what ChatGPT “knows”. As several people have noted, what would be even better is to be able to run ChatGPT on your own content. Indeed, ChatGPT itself now supports this using plugins.
I haven’t blogged for a while, work and other reasons have meant I’ve not had much time to think, and mostly I blog to help me think. ChatGPT is obviously a big thing at the moment, and once we get past the moral panic (“students can pass exams using AI!”) there are a lot of interesting possibilities to explore.